{
 "cells": [
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   "execution_count": null,
   "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Vocabulary size: 85\n",
      "Epoch 1/1 | Batch 0/78384 | train loss: 4.4383\n",
      "D: t`RRRRh.hhhgggggggppppppppyyyyy'''aaaaaa  a     a   a  a   a   a     5 555 555555iiiiiiiiiiiii\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "GGGGBBBBBBBBBKKKKBB$$$$$$fWWWWWWWWWWeeeeeKKeKKaaaaaaaaaa   a    a   a  a   a      55 55\n",
      "\n",
      "Epoch 1/1 | Batch 10/78384 | train loss: 3.2093\n",
      "Epoch 1/1 | Batch 20/78384 | train loss: 3.1261\n",
      "Epoch 1/1 | Batch 30/78384 | train loss: 3.0717\n",
      "Epoch 1/1 | Batch 40/78384 | train loss: 2.9692\n",
      "Epoch 1/1 | Batch 50/78384 | train loss: 2.8161\n",
      "Epoch 1/1 | Batch 60/78384 | train loss: 2.6699\n",
      "Epoch 1/1 | Batch 70/78384 | train loss: 2.5455\n",
      "Epoch 1/1 | Batch 80/78384 | train loss: 2.4342\n",
      "Epoch 1/1 | Batch 90/78384 | train loss: 2.3300\n",
      "Epoch 1/1 | Batch 100/78384 | train loss: 2.2368\n",
      "D:  and the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the\n",
      "\n",
      "Epoch 1/1 | Batch 110/78384 | train loss: 2.1442\n",
      "Epoch 1/1 | Batch 120/78384 | train loss: 2.0573\n",
      "Epoch 1/1 | Batch 130/78384 | train loss: 1.9725\n",
      "Epoch 1/1 | Batch 140/78384 | train loss: 1.8900\n",
      "Epoch 1/1 | Batch 150/78384 | train loss: 1.8107\n",
      "Epoch 1/1 | Batch 160/78384 | train loss: 1.7347\n",
      "Epoch 1/1 | Batch 170/78384 | train loss: 1.6595\n",
      "Epoch 1/1 | Batch 180/78384 | train loss: 1.5846\n",
      "Epoch 1/1 | Batch 190/78384 | train loss: 1.5123\n",
      "Epoch 1/1 | Batch 200/78384 | train loss: 1.4372\n",
      "D:  the children, and that she was and that she was and that she was and that she was and of the children, and that she was and and that she was and that she was and and that she was and and that she was\n",
      "\n",
      "Epoch 1/1 | Batch 210/78384 | train loss: 1.3667\n",
      "Epoch 1/1 | Batch 220/78384 | train loss: 1.2988\n",
      "Epoch 1/1 | Batch 230/78384 | train loss: 1.2240\n",
      "Epoch 1/1 | Batch 240/78384 | train loss: 1.1515\n",
      "Epoch 1/1 | Batch 250/78384 | train loss: 1.0781\n",
      "Epoch 1/1 | Batch 260/78384 | train loss: 1.0506\n",
      "Epoch 1/1 | Batch 270/78384 | train loss: 0.9384\n",
      "Epoch 1/1 | Batch 280/78384 | train loss: 0.8644\n",
      "Epoch 1/1 | Batch 290/78384 | train loss: 0.7974\n",
      "Epoch 1/1 | Batch 300/78384 | train loss: 0.7434\n",
      "D: ing to the door.\n",
      "\n",
      "Stepan Arkadyevitch was completely in the course of\n",
      "these three days.\n",
      "\n",
      "Stepan Arkadyevitch was completely in the course of\n",
      "these three days.\n",
      "\n",
      "Stepan Arkadyevitch was completely in th\n",
      "\n",
      "Epoch 1/1 | Batch 310/78384 | train loss: 0.6675\n",
      "Epoch 1/1 | Batch 320/78384 | train loss: 0.6114\n",
      "Epoch 1/1 | Batch 330/78384 | train loss: 0.5587\n",
      "Epoch 1/1 | Batch 340/78384 | train loss: 0.5119\n",
      "Epoch 1/1 | Batch 350/78384 | train loss: 0.4610\n",
      "Epoch 1/1 | Batch 360/78384 | train loss: 0.4140\n",
      "Epoch 1/1 | Batch 370/78384 | train loss: 0.3837\n",
      "Epoch 1/1 | Batch 380/78384 | train loss: 0.3542\n",
      "Epoch 1/1 | Batch 390/78384 | train loss: 0.3231\n",
      "Epoch 1/1 | Batch 400/78384 | train loss: 0.2949\n",
      "D: things cannot go on like this, that she must take some step\" to\n",
      "punish him, put him to shame, avenge on him some little part at least of\n",
      "the suffering he had caused her. She s<end><end><end><end><end><end><end><end><end><end><end><end><end><end><end><end><end><end><end><end><end><end><end><end><end>\n",
      "\n",
      "Epoch 1/1 | Batch 410/78384 | train loss: 0.2771\n",
      "Epoch 1/1 | Batch 420/78384 | train loss: 0.2623\n",
      "Epoch 1/1 | Batch 430/78384 | train loss: 0.2449\n",
      "Epoch 1/1 | Batch 440/78384 | train loss: 0.2397\n",
      "Epoch 1/1 | Batch 450/78384 | train loss: 0.2291\n",
      "Epoch 1/1 | Batch 460/78384 | train loss: 0.2203\n",
      "Epoch 1/1 | Batch 470/78384 | train loss: 0.2090\n",
      "Epoch 1/1 | Batch 480/78384 | train loss: 0.2079\n",
      "Epoch 1/1 | Batch 490/78384 | train loss: 0.1997\n",
      "Epoch 1/1 | Batch 500/78384 | train loss: 0.1962\n",
      "D:  she could hardly manage to\n",
      "look after her five children properly, they would be still worse off\n",
      "where she was going with them all. As it was, even in the course of\n",
      "these three days, the youngest was \n",
      "\n",
      "Epoch 1/1 | Batch 510/78384 | train loss: 0.1889\n"
     ]
    }
   ],
   "source": [
    "from char_rnn_beam import RNNTextGen\n",
    "\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    with open('./temp/anna.txt') as f:\n",
    "        text = f.read()\n",
    "    \n",
    "    model = RNNTextGen(text, seq_len=200)\n",
    "    log = model.fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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